A key challenge to high resolution imaging sensors used in observing terrestrial activities over a very wide field-of-view (WFOV) (e.g., 50 km2) is to achieve the resolution needed to observe and make inferences regarding events and objects of interest while maintaining the area coverage, and minimizing the cost, size, weight, and power of the sensor system. One particularly promising approach to the data deluge problem is compressive sensing, which involves collecting a small amount of information-rich measurements rather than the traditional image collection from a traditional pixel-based imager.
There is no current solution for compressive sensing architectures, especially in the infrared. An eyelid technology, liquid crystal (LC), and microelectromechanical system (MEMS) digital mirror arrays (DMA) have been postulated as potential solutions in a lab environment, but there is no current hardware available. The closest technology to production scale is a visible/short wave infrared compressive sensing camera that uses the DMA array, but this is a reflective design.
A DMA solution is limited in resolution by the number of pixels and also to a ±degree tilt in the reflective element(s). Also, the solution is complex and failure-prone due to the complex optics, and the sampling modulation is limited.